JP5094642B2 - Image processing apparatus and control method and program thereof - Google Patents

Description

  The present invention relates to an image processing apparatus, an image processing method, and a program that execute copying and transmission processing using, for example, a scanner, and more particularly to an image processing apparatus, an image processing method, and a program that use super-resolution technology.

  In recent years, there are digital copiers that read original images with a scanner and copy them using the read image data, and image processing systems that analyze image data and convert it into text data. A scanner using an image sensor such as a CCD or CIS may have a different reading resolution, that is, a modulation transfer function (MTF) of the scanner unit for each individual due to characteristics of a reading element and variations in optical processing.

  When the MTF is low, the quality of an image object that should be high definition, such as a small character, is deteriorated, and the character read by the scanner cannot be read or the character is crushed. For this reason, character extraction may fail even in optical character recognition (OCR) performed based on the read image data.

  Conventionally, each image processing apparatus manufacturer sets a quality standard for the MTF of the scanner and ships only a scanner apparatus that satisfies the standard as a product.

  Attempts have also been made to increase the MTF by performing image processing correction on an image with reduced resolution. This correction is called MTF correction, and various methods have been proposed.

  For example, in Patent Document 1, MTF correction is performed by calculating an MTF correction parameter and obtaining an MTF filter using an MTF correction chart. In Patent Document 2, in order to suppress variation in MTF of each RGB channel, MTF adjustment is performed by adjusting the focus of the CCD and the filter coefficient of the spatial filter. In Japanese Patent Laid-Open No. 2004-228688, the copy-forgery-inhibited pattern pattern is read, and an attempt is made to hold the copy-forgery-inhibited pattern component by correcting the MTF of the image data according to the detection degree of the halftone dot pattern of the read image data.

On the other hand, as a technique for correcting the resolution, there is a technique called “super-resolution” that improves the resolution by using a plurality of low-resolution images (see, for example, Patent Document 4). Super-resolution processing is a technique for generating a high-resolution image by extracting subpixels using a plurality of image data having different phases obtained from one image. If the accuracy of sub-pixel extraction is improved, an image with higher resolution can be obtained. The accuracy of the extracted sub-pixel becomes higher as the number of low-resolution image data to be adopted having different phases is larger.
JP 2000-307870 A JP 2005-45433 A JP 2007-150517 A WO2004 / 068862 Publication

  In the MTF correction using the conventional image filter as described above, the resolution of the image data itself does not increase, so that there is a limit to the MTF correction. Further, in a system using a plurality of scanners, there has been a problem that processing results for read image data may differ due to variations in MTF for each scanner. For example, the result of OCR processing of a certain document image by a certain MFP may not match the result of OCR processing of the same document image by another MFP of the same model. This is because the MTF varies depending on the individual difference of the scanner.

  Furthermore, there is also a problem that the MTF of the scanner is lowered due to aging of the light source and image sensor elements while the scanner unit is continuously used. Due to the decrease in MTF due to the change over time, the result of the reading process for one document image also changes over time. For example, there is a problem in that character information that can be recognized when it is new cannot be read over time and recognition errors increase.

  The present invention has been made in view of the above conventional example, and an object thereof is to solve the above-described problems. Specifically, the first object is to eliminate individual differences in MTF of the scanner by super-resolution processing. Secondly, an object of the present invention is to provide an image processing apparatus that can obtain an optimum image regardless of an individual by eliminating individual differences in MTF by super-resolution processing. Third, when a plurality of image reading apparatuses are introduced, the MTF between the apparatuses is constant, the variation in the reading result is suppressed, and the MTF read by any image reading apparatus is constant. The purpose is to provide. A fourth object of the present invention is to provide an image processing apparatus that suppresses changes in MTF due to changes over time and stabilizes the MTF.

In order to achieve the above object, the present invention comprises the following arrangement. The present invention provides scanner means for outputting a plurality of low-resolution image data having a first resolution and having phases shifted from each other,
A super solution for generating image data having a second resolution higher than the first resolution by using a plurality of low resolution image data having the first resolution output from the scanner unit and having phases shifted from each other. Super-resolution processing means for executing image processing;
When the resolving power of the scanner unit is smaller than the pre-designated resolving power, the super-resolution processing unit uses the resolving power of the low-resolution image data output from the scanner unit so as to be the pre-designated resolving power. Determining means for determining the number of low-resolution image data;
The super-resolution processing means uses the number of pieces of low-resolution image data determined by the determining means, and the second resolution is higher than the first resolution and the resolution of the image data having the predetermined resolution. High resolution image data having a resolution of

Alternatively, the present invention provides scanner means for outputting a plurality of low-resolution image data having a first resolution and phases shifted from each other,
A super solution for generating image data having a second resolution higher than the first resolution by using a plurality of low resolution image data having the first resolution output from the scanner unit and having phases shifted from each other. Super-resolution processing means for executing image processing;
Measuring means for measuring the resolving power of the scanner means;
When the resolving power of the scanner means measured by the measuring means is smaller than a predesignated resolving power, the super resolution is set so that the resolving power of the low resolution image data output by the scanner means becomes the predesignated resolving power. Determining means for determining the number of low resolution image data used in the resolution processing means;
The super-resolution processing means uses the number of pieces of low-resolution image data determined by the determining means, and the second resolution is higher than the first resolution and the resolution of the image data having the predetermined resolution. High resolution image data having a resolution of

  According to the present invention, the MTF of the read image data can be made constant regardless of the individual difference of the scanner and the difference of the model. As a result, it is possible to prevent a decrease in yield due to variations in the resolution of the scanner product, and to correct a change in resolution due to a change with time.

  Hereinafter, embodiments of the present invention will be described in detail with reference to FIGS. In the present embodiment, the scanner unit having a super-resolution processing function reads an image by optically scanning and super-resolutions the read image data in order to set the modulation transfer function (MTF) to the target MTF. Perform image processing. For this purpose, the image data necessary for setting the initial MTF to the target MTF based on the MTF characteristic table and the initial MTF (first resolving power index value) of the image reading apparatus by an information processing apparatus such as a computer. Determine the number. Here, in the MTF characteristic table, in order to set the measured initial MTF value (first resolving power) as the target MTF value, the low-resolution image data having the first resolution required in the super-resolution processing is stored. It is a table that associates (or associates) numbers with initial MTFs. In the MTF characteristic table, the number of sheets is registered in association with a plurality of different initial MTFs for each type (model) of the image reading apparatus. The MTF characteristic table is created by an information processing apparatus such as a computer.

  Here, the initial MTF value is an MTF when image data is output without performing super-resolution processing. Then, according to the initial MTF value, the number of low-resolution image data used for the super-resolution processing is determined with reference to the MTF characteristic table and stored in the image processing apparatus. The scanner unit performs super-resolution processing on the determined number of low-resolution image data having the first resolution, and generates high-resolution image data having a second resolution higher than the first resolution. To do.

  In the description of the present embodiment, a modulation transfer function (MTF) is used as the resolution (or resolution) of an image scanner (also simply referred to as a scanner) that is an image reading apparatus. The unit of MTF used in the present embodiment is percent, and shows a relationship that the input and the output are equal when the MTF value is 100 (%). The MTF is an index value indicating how faithfully the original image to be read can be reproduced, and is indicated by, for example, the ratio of the contrast of the read image data to the contrast of the original image. That is, if the MTF is 1 (= 100%), it indicates that the read document image is completely reproduced as image data. Since the MTF can vary depending on the frequency, it is generally expressed as a frequency characteristic using the spatial frequency as a parameter. However, the MTF for a predetermined spatial frequency may be treated as the MTF of the apparatus. For example, in the present embodiment, since the MTF is used as an index of the resolution of the scanner, it is possible to read a sample image having a spatial frequency corresponding to a predetermined target resolution, measure the MTF of the image data, and use the value.

<Configuration of image processing apparatus>
FIG. 1 is a block diagram of an image processing apparatus according to an embodiment of the present invention, for example, a digital multifunction peripheral. A scanner unit 101 is a part that reads a document and converts it into image data. The scanner unit 101 has a mechanism for efficiently reading low-resolution image data to be used for super-resolution processing, and executes high-resolution image data (image data of a designated resolution in this embodiment) by executing super-resolution processing. Output is possible. Details will be described later with reference to FIGS. The CPU 102 performs various controls of the image processing apparatus. The RAM 103 has a work area for developing programs for various controls of the CPU 102 and a non-volatile area, and stores various parameters for reading processing. The ROM 104 stores various control programs executed by the CPU 102. The recording unit 105 is a part that records image data read by the scanner unit 101 and subjected to image processing on a recording medium. The operation unit 106 gives an instruction for the operator to start document reading control, and displays the state of the image apparatus and various errors. The communication unit 107 communicates with an external device through a network.

  FIG. 2 is a block diagram showing a configuration of the scanner unit 101 of the image processing apparatus according to the first and second embodiments of the invention. As shown in FIG. 2, in the scanner unit 101, the image data read from the area sensor 10 is super-resolution processed by the super-resolution processing unit 11 according to the parameters set in advance by the super-resolution parameter setting unit 12. The Thereby, image data after the super-resolution processing is generated. Thereafter, the read image data is stored in the generation RAM 102 or the recording unit 105 through the image processing unit 14 that performs attribute determination of the read image.

<Configuration of scanner unit>
FIG. 26 shows a configuration of the scanner unit (also referred to as an image reading unit) 101. In FIG. 26, the auto document feeder 2602 has an ADF function that suppresses the original image data and sends the original 2603 to the original reading position when performing the flow reading. A platen glass 2604 is a glass plate on which the document 2603 is placed when the document table is read. A reading unit 2605 includes a light source 2606, a reading device (that is, an image sensor) that reads an original image on the original 2603, and the like, and moves in the sub-scanning direction to scan the original 2603. A light source 2606 is a white light source such as a xenon tube, and irradiates a portion to be read on the document 2603 with white light. The mirrors 2607 to 2611 have a role of guiding the reflected light of the light source light from the document to the image sensor 2613. The image sensor 2613 is the same as the area sensor 10 of FIG. A lens 2612 is a lens for condensing the reflected light of the document data reflected by the mirror 2611 on the image sensor 2613. The image pickup element 2613 is an image pickup element in which elements that output an image of a formed original image as, for example, a charge corresponding to luminance are arranged in a planar shape. In the present embodiment, the element arrangement in the image pickup element 2613 is a grid arrangement in which a single line has a length that covers the maximum width of an original that can be read, and a plurality of such lines are arranged so that there is no displacement in pixel positions. . In the present embodiment, the image sensor is fixed to the reading unit 2605 at a slight angle so that the lines do not intersect with the sub-scanning direction.

  FIG. 28 shows an example of the image sensor 2613. In FIG. 28, the sensor of 10 lines is shown instead of 3 lines. However, for example, if 3 lines of the uppermost line, the lowermost line, and an intermediate line thereof are used, the sensor of FIG. 2 is obtained.

  In this embodiment, the image sensor 2613 is arranged in a grid of 20 pixels in the main scanning direction and 10 pixels in the sub-scanning direction, and the image sensor 2613 spreads in the line direction of the element arrangement and the direction orthogonal thereto. It has an area sensor. The area sensor is mounted with an inclination with respect to the reference installation position. The reference installation position is a position where the line is perpendicular to the sub-scanning direction in which the reflected image from the document moves. In a normal copying machine or scanner, the reference installation position is the reference installation position. The image sensor 2613 is fixed. In this case, the pixel column read in each line becomes the pixel column on the main scanning line as it is. In this embodiment, the installation is performed with an angle θ with respect to the reference installation position. That is, the sub-scanning direction and the line direction are orthogonal to each other at the reference position, whereas at the position shown in FIG. 28, the sub-scanning direction and the line direction form an angle of (90 + θ) degrees. In this case, the inclination of the line is corrected on the image data, and image data in which pixels are arranged in the orthogonal coordinate system is obtained for the first time.

  In FIG. 28, the position of the constituent pixel sensor 2613 is represented with the upper left end of the area sensor as the origin, the main scanning direction as the x direction, and the sub scanning direction as the y direction. That is, the coordinates at the upper left end are (x, y) = (0, 0), and the coordinates at the upper right end are (x, y) = (19, 0). Similarly, the coordinates of the lower left end are (x, y) = (0, 9), and the coordinates of the lower right end are (x, y) = (19, 9).

  A line 2803 indicates a group of pixel sensors for one line constituting the area sensor 2801. Specifically, it is composed of 20 pixel sensors constituting the main scanning direction. That is, it is composed of pixel sensors at coordinate positions (0, 4), (1, 4), (2, 4), ... (19, 4). In the following description, a plurality of pixel sensors indicated by a line 2803 are referred to as a read line sensor 2803. Similarly, the line 2804 is composed of pixel sensors at coordinate positions (0, 5), (1, 5), (2, 5),... (19, 5). Called.

  In the present embodiment, the reading unit 2605 including the area sensor 2613 mounted on the reading unit 101 is driven in the sub-scanning direction shown in FIG. 28 to read the document image placed on the document table 2604. That is, the reading operation is performed by treating the reading line sensors 2803 and 2804, which are a group of pixel sensors, as independent line sensors.

  Next, how the image data read by the reading line sensor 2803 and the reading line sensor 2804 will be described. In this description, it is assumed that an image to be read is a letter “A” of the English alphabet drawn on a full sheet.

  The document image is read by the image sensor 2613, but the image sensor 2613 (that is, each line sensor) is inclined at an angle θ, whereby image data in which each line is inclined at an angle θ is obtained. The read image data is directly stored in a storage medium such as a memory.

  Image data detected and read by each line sensor of the image sensor 2613 is data as shown in FIGS. 29A and 29B, and both are read as image data inclined at an angle θ. FIG. 29 is an example of image data read by two different line sensors 2803 and 2804, respectively. As shown in FIG. 28, the reading line sensor 2803 and the reading line sensor 2804 are physically shifted by one pixel in the sub-scanning direction. Therefore, there is a phase shift (or position shift) between the pixel sensor constituting the reading line sensor 2803 and the pixel sensor constituting the reading line sensor 2804 with respect to the horizontal direction and the vertical direction. For example, the pixel sensor located at the coordinates (x, y) = (15, 4) of the reading line sensor 2803 and the pixel sensor located at the coordinates (x, y) = (15, 5) of the reading line sensor 2804 are: The position in the y-axis direction is shifted by y = 1 pixel. The shift causes a shift of Δβ (pixel) <1 (pixel) in the sub-scanning direction.

  On the other hand, the position in the x-axis direction is exactly the same x = 15. However, when viewed in the horizontal direction, which is the main scanning direction before the entire area sensor is tilted by the tilt angle θ, the phase is shifted by a minute amount Δα within the sub-pixel. In other words, even if the elements are located at the same position in the x-axis direction among a plurality of line sensors, tilting the imaging element 2613 causes a minute phase shift depending on the tilt angle in the main scanning direction and the sub-scanning direction. To do.

  Therefore, image data read by a plurality of adjacent line sensors defined in the image sensor 2613 have the same resolution and have phase shifts of less than one pixel. Specifically, the read image data in FIG. 29A and the read image data in FIG. 29B are not only shifted by Δβ in the sub-scanning direction, but also shifted in phase by Δα in the main scanning direction. It has become.

  In the above description, it is assumed that there are two reading line sensors (reading line sensors 2803 and 2804), but the present invention is not limited to this. A large number of reading line sensors may be configured by increasing the number of pixel sensors constituting the image sensor 2613 in the x-axis direction. In other words, the maximum number of read line sensors is equal to the number of pixels arranged in the x-axis direction constituting the image sensor 2613. The number configured as the reading line sensor is equal to the number of read image data obtained by one reading operation. That is, if 30 reading line sensors are configured in the image sensor 2613, 30 read images having different phase shifts can be obtained by one reading control. By tilting the image sensor 2613, a plurality of images in which the deviation in the main scanning direction is less than one pixel in the image data of a plurality of lines adjacent to the document image in the sub-scanning direction by scanning the document image once. Minute image data can be obtained.

  As described above, since the image pickup element 2613 is tilted and the interval between the line sensors is large, image data whose phase is shifted in the main scanning direction and the sub-scanning direction can be obtained for each channel. If the phase shift is in sub-pixel units, super-resolution processing can be performed using those image data, and a high-resolution image can be acquired. By adjusting the interval and angle of the sensors, it is possible to make the phase shift sub-pixel unit. However, even if the phase shift exceeds one pixel, if the positional shift at both ends of the line is excluded, the shift in pixel units is subtracted and reduced to a sub-pixel shift, which can be used for super-resolution processing. .

  In FIG. 28, the image sensor 2613 reads two lines of image data, and outputs two pieces of image data that are out of phase with each other in a single scan. However, this is for explanation, and if the number of lines in which the amount of phase shift falls within one pixel is n lines, for example, as shown in FIG. 4, low-resolution image data having a maximum of n phase shifts. Can be output.

<Super-resolution processing>
Next, the super-resolution processing in the super-resolution processing unit will be described using the schematic diagram of FIG. 4 and the flowchart of FIG. Since the super-resolution processing itself is an existing technology, only an outline thereof will be described. As shown in FIG. 4, the super-resolution processing unit performs super-resolution processing using a plurality of low-resolution image data having different phases. A plurality of low-resolution image data is used for super-resolution, but the greater the number of low-resolution image data used, the higher the pixel extraction accuracy of the generated high-resolution image data. This is because, as shown by the shaded portion 401 in FIG. 4, if the number of low-resolution image data is large, the amount of information per pixel calculated for the high-resolution image data increases. As a processing flow, a set number of low-resolution image data is acquired from the area sensor 10 (S500), and super-resolution processing is performed using the low-resolution image data (S501). Note that image data is handled as, for example, a data file, but normally corresponds to one image. Therefore, in the present embodiment, the number of image data is referred to as “number of sheets”.

  In the present embodiment, a plurality of low resolution images are acquired using the area sensor 10 arranged as shown in FIG. However, some other methods are conceivable as methods for obtaining a plurality of low-resolution images. For example, it is possible to select different information by using pixel information to be acquired as separate lines or using an array state of pixels (for example, a Bayer array). A plurality of pixels can be extracted as one pixel data. These methods can also stably acquire low-resolution images with different phase information.

  The super-resolution processing unit 11 performs super-resolution processing based on a predetermined set number of pieces of low-resolution image data to generate high-resolution image data. The input low-resolution image is image data having different phases. If the number of inputs is large, the sub-pixel extraction accuracy of the generated high-resolution image data is improved, and a higher resolution and higher MTF (resolution) image is obtained. Data can be generated. FIG. 6 is a table showing the correspondence between each image processing apparatus and the type of scanner (scanner type) attached thereto in the description of this embodiment.

  The super-resolution processing unit 11 performs the super-resolution processing in response to the super-resolution processing parameters set by the super-resolution parameter setting unit 12, specifically, the number of images used for the super-resolution processing. . The super-resolution parameter setting unit 12 reads parameters from the super-resolution parameter storage unit 13 that stores the number of images necessary for super-resolution. There is also a data flow from the area sensor 10 to the image processing unit 14. This system is an image processing flow that does not perform super-resolution processing, and is used for measurement of initial MTF.

  FIG. 3 is a diagram showing the contents included in the ROM and RAM of the image processing apparatus according to this embodiment. The ROM 104 stores programs and data such as a super-resolution processing program 200, an image reading processing program 201, a resolution measurement processing program 202, and a communication processing program 203. In the RAM 103, a work area 204 is secured, and an image number 205 and a target MTF 206 determined by a procedure described later are stored. These parameters have a relationship that super-resolution processing using low-resolution image data of the number given by the number of images 205 is necessary to achieve the target MTF 206, and a set of these values is set in the MTF characteristic table 207. Call it. The RAM 103 also includes identification information 208 indicating the type of scanner unit.

  The super-resolution processing will be exemplarily described with reference to FIGS. 30 and 31. FIG. Here, the low-resolution image data to be processed is a diagram illustrating low-resolution image data used for super-resolution processing and high-resolution image data after super-resolution processing, as shown in FIG. Images F0 to F3 shown on the left side of FIG. 30 are low resolution image data. It is assumed that these low resolution image data have already been obtained.

  The inclination angle θ of the image sensor 2613 is held in a storage area inside the multifunction device as a value unique to the mounted device. In the super-resolution processing of the present embodiment, the angle information is used to perform affine transformation, and the obtained obliquely tilted image data is rotated, and the image data is compensated so as to reduce the tilt with respect to the scanning direction. To correct the tilt of the image data.

If the coordinates before conversion are (X, Y), the coordinates after conversion are (X ′, Y ′), and the rotation angle (inclination angle of the area sensor in this embodiment) is θ, an affine as shown in Equation 1 is obtained. Image data with the tilt corrected by the conversion process can be obtained. Let X, Y be the coordinates of the pixel before conversion, and X ′, Y ′ be the coordinates after conversion.
[X ′, Y ′, 1] = [X, Y, 1] | cos θ sin θ 0 |
| −sin θ cos θ 0 |
| 0 0 1 | ... Formula 1
In the above equation, the right term on the right side is a 3 × 3 matrix.

  The image data obtained by the affine transformation is low-resolution image data whose inclination is corrected. The method for correcting the inclination is not limited to affine transformation, and any method that can correct the inclination of the image data may be used.

  Then, the super-resolution processing is performed using a plurality of low-resolution image data whose inclination is corrected, and processing is performed.

  FIG. 30 shows a document and reference low resolution image data F0 obtained by reading the document with an area sensor and other low resolution image data (referred to as target low resolution image data) F1 to F3. A dotted rectangle surrounding the document indicates an area when the reference low resolution image data F0 is read by the area sensor, and a solid line rectangle indicates an area when each of the target low resolution image data F1 to F3 is read by the area sensor.

  In the present embodiment, for the sake of clarity in FIG. 30, the shift of each target low resolution image is shown as being in units of one pixel. However, in actual reading by the area sensor, 1 in the main scanning direction and the sub scanning direction. There is a phase shift less than a pixel. By using this minute shift, high resolution can be achieved.

  Among the pixels (hereinafter referred to as “generated pixels”) constituting the generated high resolution image data, there are pixels that are not present in either the reference low resolution image or the target low resolution image.

  For such pixels, high resolution is achieved while synthesizing by performing predetermined interpolation processing using pixel data representing pixel values of pixels existing around the generated pixel. As the interpolation process, an interpolation process such as a bi-linear method, a bi-cubic method, or a near-less staver method can be used. An example is shown in FIG.

For example, when using the interpolation processing by the bilinear method, first, the nearest pixel 1802 that is closest to the position of the generation pixel 1801 is extracted from the reference low resolution image and the target low resolution image data. Then, the four pixels surrounding the generated pixel position are determined as the peripheral pixels 1802 to 1805 from the target low resolution image in FIG. 31, and the values obtained by adding a predetermined weight to the data values of the peripheral pixels are averaged, and The data value of the generated pixel is obtained.
f (x, y) = [| x1-x | {| y1-y | f (x0, y0) + | y-y0 | f (x0, y1)} + | x-x0 | {| y1-y | f (x, y0) + | y-y0 | f (x1, y1)}] / | x1-x0 || y1-y0 |.

  By repeating the above processing for each generated pixel position, for example, a super-resolution image having a double resolution shown in FIG. 30 can be obtained. Note that the resolution is not limited to double and can be various magnifications. In addition, as the data values of a plurality of low resolution images are used for the interpolation processing, a higher definition super resolution image can be obtained.

  Furthermore, the super-resolution processing can be performed in units of blocks constituting an image. Further, the above-described determination of the number of low-resolution image data can be performed in units of blocks.

  Now, a specific processing example of the present invention using the image processing apparatus will be described.

[Embodiment 1]
First, an image processing system according to a first embodiment of the present invention, which corrects MTF variation by setting the number of super-resolution processing at the time of shipment of the scanner and outputs stable scan data, will be described. This image processing system includes an information processing apparatus such as a computer and an image processing apparatus such as a scanner, which are preferably connected to each other. This is because it is possible to collect information from the scanner and send information to the scanner online, but input / output information even when they are not connected to each other or offline. If possible, this embodiment can be realized.

<Extraction of MTF characteristics according to scanner type>
In an image processing apparatus such as a digital multi-function peripheral (MFP), various reading apparatuses are used. Here, in order to be able to specify the variation characteristic of the reading and resolving power, the variation characteristic of the MTF is extracted for the same type (scanner type) scanner.

  First, a target value of MTF is set in advance. This target value is input from the operation unit 106 and stored in the target MTF area 206, for example. Here, the target value of MTF of the scanner unit (scanner type 100) installed in the multi-function peripheral (MFP) -A is set to 60 (%).

  Next, a procedure for creating the MTF characteristic table of the scanner type 100 will be described with reference to the flowchart of FIG. This procedure is executed by an operator or the like using the image processing apparatus and the MTF measuring apparatus.

  First, in order to measure the variation of the initial MTF in the scanner type 100, the MTF of the scanner type 100, that is, the initial MTF is measured without performing super-resolution processing. Specifically, using an image processing apparatus using the scanner type 100, the scanner unit of FIG. 2 reads an MTF measurement chart using a system that does not perform super-resolution processing, and generates image data ( S100). Then, the MTF value of the scanner type 100 is measured using the generated image data and the MTF measuring device (S101). By the procedure so far, the MTF value in the initial state of the scanner type 100 is determined. The initial MTF value is registered in the MTF characteristic table as the initial MTF value of the scanner unit. Registration can be performed by, for example, a general-purpose computer. The scanner can specify whether or not to perform super-resolution processing, and processing is performed according to the specification. This designation is valid only at the time of manufacture. For example, it may be configured to always perform super-resolution processing as invalid for a product to be shipped.

  Next, the super-resolution process is performed, and the necessary number of low-resolution images required for the super-resolution process until the target MTF is reached is acquired. Specifically, the super-resolution processing unit 11 performs super-resolution processing using the image data output from the area sensor 10 as low-resolution image data (S102). Further, the number of images input to the super-resolution processing is increased, and it is measured whether the generated image data has reached the target MTF. For this reason, initially, the number of super-resolution image data starts from, for example, two. However, as a method for knowing the MTF characteristics of the scanner type 100, as shown in FIG. 8, super-resolution processing is performed for each number of low-resolution image data used for super-resolution processing when super-resolution processing is performed. It is possible to generate super-resolution images according to the number of images used at one time. The MTF of the high-resolution image data generated in this way is measured using the MTF measurement system (S103). Then, it is determined whether the measured value has reached the target MTF (S104). If the target MTF is reached as a result of the determination, the number of low-resolution image data used to create the high-resolution image data is low enough for the super-resolution processing for setting the resolution of the scanner unit to the target resolution. This is the number of resolution image data. As a result, the necessary number of super-resolution images for reaching the target MTF in the scanner type 100 is calculated (S106). This number is stored as the number of images in the MTF characteristic table in association with the initial MTF.

  Of course, this number is not a number applicable to all scanner type 100 scanners, and needs to be determined for each scanner type 100 scanner in order to eliminate individual differences. Therefore, the number of images necessary for the super-resolution image is acquired for a plurality of scanner types 100 as well.

  On the other hand, if the target value has not been reached, the number of low-resolution image data is further increased (S105), and super-resolution processing is attempted again. At this time, the number of low-resolution image data to be increased can be predicted from the difference between the measured MTF value and the target MTF value, and can be increased by the predicted number.

  As a result of the above processing, a table of the number of low-resolution images necessary for the super-resolution processing for the initial MTF and the target MTF according to the variation characteristics of the scanner type 100 is generated.

  FIG. 9 is a schematic diagram showing the flow of the above description. MFP-A, MFP-B, and MFP-C are image processing apparatuses each equipped with a scanner type 100. The initial MTF value in MFP-A was 30, the initial MTF value in MFP-B was 40, and the initial MTF value in MFP-C was 55.

  Further, as a result of performing the super-resolution processing to reach the target MTF 60, the required number of images in MFP-A is 40, the required number of images in MFP-B is 28, and the required number of images in MFP-C is 10. It was. As a result, the MTF characteristic table 901 of the scanner type 100 in FIG. 9 is created. This MTF specifying table is duplicated in a memory (for example, ROM) of the scanner unit of the scanner type 100, and the scanner unit obtains the number of sheets corresponding to the initial MTF of the scanner unit measured separately from the MTF characteristic table, and the number of sheets. Super-resolution processing is performed using the low-resolution image data.

<Super-resolution parameter setting procedure in the shipping process>
Next, the procedure at the time of shipment of the image processing apparatus using the scanner type 100 will be described with reference to the flowchart of FIG. 10 and the schematic diagram of FIG. In the shipping process, the image processing apparatus stores the MTF characteristic table 207 created by the procedure shown in FIG. 7 as shown in FIG. In this example, it is assumed that the MTF characteristic table 901 is stored. Further, the MTF of the scanner unit of the image processing apparatus using the scanner type 100 is measured. Specifically, the MTF of the scanner in the initial state is measured using the MTF measurement chart as in the case of extracting the MTF characteristics (S200 → S201).

  Here, for example, it is assumed that the MTF value in the image processing apparatus 300 equipped with the scanner type 100 is 45. In that case, the necessary number of images used for the super-resolution processing corresponding to the MTF value 45 is obtained from the MTF characteristic table 901 of the scanner type 100 generated by the procedure of FIG. Specifically, the MTF value closest to the initial MTF of the scanner unit to be measured is searched with reference to the initial MTF value in the MTF characteristic table 901 of FIG. If there is a table having exactly the same value, the value (number) of the table corresponding to the initial MTF is used as the number of images necessary for correction. If there is no same value, the number of images registered in the table corresponding to the MTF values before and after that value is linearly complemented to calculate the number of images. If there are no values before and after, linear interpolation is performed using the number corresponding to the closest value and the next closest value.

  With the above procedure, the number of images necessary for the super-resolution processing to obtain the target MTF in the image processing apparatus 300 is calculated (or determined) (S202). The value determined here is stored in the image number storage area 205 of the nonvolatile RAM as a reading parameter of the image processing apparatus 300 (S203).

  In this example, the entire procedure of FIG. 10 is executed by an information processing apparatus such as a computer, and the obtained number is registered in the image processing apparatus. However, for example, the initial MTF value measured in step S201 may be registered in the image processing apparatus, and the image processing apparatus may execute steps S202 and S203 to determine the number of sheets.

<MTF correction processing in the environment used by the user>
Finally, the MTF correction processing when the user actually uses the image processing apparatus will be described with reference to the block diagram of the scanner unit in FIG. 2, the flowchart in FIG. 12, and the schematic diagram in FIG. The flow in FIG. 12 is executed by the image processing apparatus. When an operator designates a function such as copy or fax and the reading process is activated, the reading process is performed, and the super-resolution process 11 of FIG. 2 is performed.

  In this super-resolution processing, the number of images stored in the number-of-images storage area 205 in the shipping process (for example, a value of 26) is set from the super-resolution parameter setting unit 13 to the super-resolution processing unit 12 (S301). Then, super-resolution processing is performed (S302). As a result, the image data generated by the super-resolution processing unit 13 becomes image data that satisfies the MTF set as the target (S303), and is passed to the image processing unit 14.

  In the description of the above embodiment, adjustment in a plurality of channels (for example, each color component plane in the case of a color scanner) is not mentioned, but the same can be done in the case of color reading. However, the target value of MTF and the number of images necessary for super-resolution processing are required for each reading channel such as RGB and K.

  With the above configuration and procedure, it is possible to eliminate individual differences in the resolving power of the scanner unit and manufacture a product that has uniformly achieved the target resolving power. For this reason, the manufacturing yield of the scanner can be improved.

[Embodiment 2]
Next, a method according to the second embodiment of the present invention, in which the target reading MTF values are matched within the same group and the reading accuracy within the group is made constant will be described. In the present embodiment, the same processing is performed until the shipping process of the first embodiment, and thus detailed description is omitted.

<Super-resolution parameter setting procedure in the shipping process>
The parameter setting procedure in the shipping process will be described with reference to the flowchart of FIG. 14 and the schematic diagram of FIG. In the shipping process, the image processing apparatus 301 acquires an image using the MTF measurement chart (S400), and the MTF measurement apparatus measures the MTF (S401). As a result, an initial reading MTF value (for example, 50) is obtained. Then, the required number of low-resolution image data for the initial read MTF value is calculated from the MTF characteristic table of a scanner (scanner type 200 in this example) that is a reading device mounted on the image processing apparatus 301. As a result, for example, a result of 16 sheets is obtained.

Therefore, the image processing apparatus 301 stores the following parameters in the nonvolatile RAM as reading parameters (S403).
-Scanner type indicating the type of scanner: 200,
-Initial MTF value: 50,
-Target MTF value: 70,
The number of images corresponding to the target MTF value: 16.

<MTF adjustment method within group>
Next, a method for adjusting the MTF within the group will be described. It is assumed that a plurality of MFPs, scanner devices, and control PC 400 described in the present embodiment are configured as shown in FIG. That is, the MFP 301 and the like constituting the group and the control PC 400 are connected to each other via a network. In this embodiment, an application installed in the control PC 400 is used to perform MTF adjustment. Specifically, the operator activates an application for MTF adjustment on the control PC 400 and executes the adjustment. Hereinafter, the MTF adjustment procedure will be described in order.

  First, a group in which the user performs MTF adjustment is registered in the control PC 400 in advance. Then, the MTF adjustment is started when the user performs an MTF adjustment start operation from the control PC 400. This will be described in detail below with reference to the MTF characteristic table of FIG. 15, the sequence diagram of FIG. 18, and the flowcharts of FIGS.

  FIG. 19 is a flowchart showing processing in control PC 400. FIG. 20 is a flowchart showing processing in the image processing apparatus 301 that receives MTF adjustment. The control PC 400 issues an acquisition request for each MTF correspondence table to each MFP / scanner apparatus registered in the group (S600).

  Each MFP / scanner apparatus receives the MTF adjustment request (S700), and transmits its own MTF parameter information (initial MTF, target MTF, required number of images) and its own scanner type information. (S701).

  The control PC 400 receives the MTF parameter information and the scanner type from the MFP / SFP in the group (S601). Then, the MTF characteristic table is developed according to the sent scanner type (S602). In step S602, the MTF adjustment application determines and stores the lowest target MTF in this example as the common target MTF of the group among the target MTFs registered for each scanner in the group. When the MTF parameter information of the scanners belonging to the group is as shown in FIG. 21, since 60 is the lowest MTF, the adjusted target MTF value is 60. Of course, it is possible to select another determination method such as setting the highest MTF, setting an average value, or setting a mode value. In this example, in an MFP / scanner apparatus using a scanner with a low target MTF, if a new target value higher than that is set, the load of super-resolution processing increases. Therefore, in this embodiment, the lowest target value is set. Is set.

  For the newly set target MTF, the MTF adjustment application refers to the MTF characteristic table for each sent scanner type, and calculates a new number of images for the target MTF (S603). This is performed in the same manner as in the first embodiment. The calculation formula in this case is (new target MTF value / previous target MTF value) * (previous number of images). In the present embodiment, since the new target MTF value is set to 60, the number of images necessary for the super-resolution processing in the image processing apparatus 301 of the scanner type 200 is (60/70) * 16 = 13.714. Since it is the number of sheets, it is advanced to 14 sheets. When the number of images necessary for the super-resolution processing for the target MTF is newly calculated, the image number information is transmitted from the control PC to each MFP / scanner apparatus (S604). Further, the number of previous images is notified as it is to the image processing apparatus in which the target MTF does not change.

  In the control PC 400, if the MTF characteristic table is created and stored in the procedure of the first embodiment for all scanner types belonging to the group, the low resolution image data corresponding to the new target MTF is stored. Can be determined again in the manner of the first embodiment.

  In response to the notification of the number of images, each MFP / scanner device overwrites the received target MTF value and the required number of low-resolution images on the table value of the own device. For example, the image processing apparatus 301 receives a new image number setting from the control PC 400 (S702), and stores the image number in the nonvolatile RAM (S703).

  After the above-described adjustment control, when the reading process is performed by the operator in the MFP / scanner apparatus in the group, the super-resolution process for the newly set number of low-resolution images is performed, which is unified within the group. The target MTF image data is generated.

[Embodiment 3]
Next, the MTF of the image data generated by changing the number of low-resolution images in the super-resolution processing is constant with respect to the MTF deterioration due to the change of the scanner over time, which is the third embodiment of the present invention. How to keep is explained. The scanner unit of the image processing apparatus according to the present embodiment is configured as shown in FIG. A resolution measuring unit 24 is provided at the subsequent stage of the super-resolution processing unit 11, and the MTF value can be measured during the reading process. In the present embodiment, the same processing is performed up to the shipping process of the first embodiment, and thus detailed description thereof is omitted.

<Super-resolution parameter setting procedure in the shipping process>
The parameter setting procedure in the shipping process will be described with reference to the block diagram of the scanner unit in FIG. 22, the flowchart in FIG. 23, and the schematic diagram in FIG. In the shipping process, the MTF measurement chart is read by the image processing apparatus 302 (S800), and the MTF is measured by the MTF measurement apparatus (S801). As a result, it is assumed that the initial read MTF value is 50. Then, from the MTF characteristic table of the mounted scanner type 200, the number of images required for the super-resolution processing at the initial MTF value 50 is calculated with respect to the target MTF value (for example, 70) (S802), as shown in FIG. Thus, for example, a result of 16 sheets is calculated.

  At that time, the image processing apparatus 302 stores, as reading parameters, the number of images 16 necessary for the super-resolution processing corresponding to the target MTF value and the MTF characteristic table corresponding to the scanner type of the own device in the nonvolatile RAM. (S803). As described in the first embodiment, the MTF characteristic table is a table including a plurality of sets of images necessary for super-resolution processing for the initial MTF and the target MTF for each scanner type. The MTF characteristic table indicates the initial MTF variation in the scanner type and the number of images necessary for the corresponding super-resolution processing.

<MTF correction processing in the environment used by the user>
Immediately after shipment, at the time of image reading by the image processing apparatus 300, super-resolution processing is performed based on the number of low-resolution images stored in the own apparatus to generate image data. The process up to this point is the same as in the first embodiment.

  Next, a description will be given of the MTF correction processing when the usage period has passed to some extent in the user usage environment and the MTF of the read image has decreased due to deterioration of the reading element and light source of the scanner. In this embodiment, the start of MTF correction is started by the user, but when a preset number of reading processes are performed, a display prompting the correction process may be displayed. In the present embodiment, the user measures the current MTF value using the MTF measurement chart. This will be described below with reference to the block diagram of FIG. 22 and the flowchart of FIG.

  First, the user instructs the start of MTF correction (S900). Then, the MTF measurement chart is read from the scanner unit (S901). The read image data is transferred from the area sensor 10 in FIG. 22 to the MTF measurement unit 24. The MTF measurement method calculates the resolving power of the reading unit from the reading result of the measurement chart by using a predetermined measurement chart (S902). The details of the MTF measurement method may be the same as those in the first embodiment, and will not be described in detail here because it is not the main point of the present application.

  When the current MTF value is calculated from the MTF measurement chart, the number of images required for super-resolution processing is calculated using the MTF characteristic table to reach the target MTF (S903). Here, the case where the initial MTF value has decreased from 45 at the time of shipment to 45 will be described. In this case, the number of low-resolution image data for the MTF value 45 is calculated using the MTF characteristic table stored in the nonvolatile RAM. Similarly to the calculation of the number of images so far, calculation is performed by linear calculation from the closest value. For example, the required number of images is calculated as 25 from the MTF characteristic table of FIG. As a result of the calculation, the number of images required for the super-resolution processing is calculated as 25, and this is stored as a new value for the number of images 205 in the nonvolatile RAM (S904).

  Thereafter, when a new reading process is performed, a super-resolution process is performed using the newly set number of images. Therefore, the MTF deteriorated due to the change with time is corrected, and the image data that is the same MTF as at the time of shipment is obtained. To be able to get.

  The super-resolution processing of the embodiment may use the method of WO2004-068862. Processing performed by a computer, for example, processing such as generation of an MTF characteristic table, may be performed by an image processing apparatus instead of a computer.

  Further, the present invention can be applied to a system (for example, a copier, a facsimile machine, etc.) consisting of a single device even when applied to a system composed of a plurality of devices (for example, a host computer, interface device, reader, printer, etc.). You may apply. Another object of the present invention is to supply a recording medium recording a program for realizing the functions of the above-described embodiments to a system or apparatus, and for the computer of the system or apparatus to read and execute the program stored in the storage medium. Is also achieved. In this case, the program itself read from the storage medium realizes the functions of the above-described embodiment, and the program itself and the storage medium storing the program constitute the present invention.

  In the present invention, the operating system (OS) running on the computer performs part or all of the actual processing based on the instructions of the program, and the functions of the above-described embodiments are realized by the processing. This is also included. Furthermore, the present invention is also applied to a case where a program read from a storage medium is written in a memory provided in a function expansion card inserted into a computer or a function expansion unit connected to the computer. In that case, based on the instruction of the written program, a CPU or the like provided in the function expansion card or function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

1 is a block diagram of an image processing apparatus according to an embodiment of the present invention. It is an internal block diagram of the scanner part of Embodiment 1, 2 of this invention. It is a figure which shows the content of ROM / RAM concerning embodiment of this invention. It is a figure which shows the outline of the super-resolution process concerning embodiment of this invention. It is a follow chart of the super-resolution process concerning embodiment of this invention. 5 is a correspondence table between image processing apparatuses and scanner types according to an embodiment of the present invention. It is a flowchart which shows the production | generation process of the MTF characteristic table concerning embodiment of this invention. It is the schematic which shows the production | generation method of the super-resolution image data concerning embodiment of this invention. It is the schematic which shows until the MTF characteristic table concerning embodiment of this invention is produced | generated. It is a flowchart of the super-resolution parameter setting in the shipping process in Embodiment 1 of the present invention. It is a figure which shows the outline of the super-resolution parameter setting in the shipment process in Embodiment 1 of this invention. It is a flowchart which shows the MTF correction process at the time of user use in Embodiment 1 of this invention. It is a figure which shows the outline of the operation | movement at the time of user use in Embodiment 1 of this invention. It is a flowchart which shows the super-resolution parameter setting procedure in the shipment process in Embodiment 2 of this invention. It is a figure which shows the outline of the super-resolution parameter setting in the shipment process in Embodiment 2 of this invention. It is a system configuration figure in Embodiment 2 of the present invention. It is a figure which shows GUI of the MTF adjustment application in Embodiment 2 of this invention. It is a figure which shows the sequence of MTF adjustment in Embodiment 2 of this invention. It is a MTF adjustment flowchart of control PC in Embodiment 2 of this invention. It is a MTF adjustment flowchart of the image processing apparatus in Embodiment 2 of the present invention. It is the figure which showed the state of the MTF characteristic table on M control PC in Embodiment 2 of this invention. It is a block diagram of the scanner part of the image processing apparatus in Embodiment 3 of this invention. It is a flowchart which shows the super-resolution parameter setting procedure in the shipment process in Embodiment 3 of this invention. It is the schematic which shows the super-resolution parameter setting procedure in the shipment process in Embodiment 3 of this invention. It is a flowchart of the MTF correction process by the user in Embodiment 3 of this invention. It is a figure which shows the cross section of an image reading part. It is a figure which shows an example of a super-resolution process. It is a figure which shows the example of arrangement | positioning of an image pick-up element. It is a figure which shows an example of the low-resolution image data imaged and read of FIG. It is a figure which shows an example of a super-resolution process. It is a figure which shows an example of a super-resolution process.

Explanation of symbols

10. Area sensor 11 of image processing apparatus according to first and second embodiments 11 Super-resolution processing unit 12 of image processing apparatus according to first and second embodiments Super-resolution parameter setting unit 13 of image processing apparatus according to first and second embodiments Super-resolution parameter storage unit 14 of the image processing devices 1 and 2 Image processing unit 20 of the image processing device of the first and second embodiments Area sensor 21 of the image processing device of the third embodiment Super image processing device of the third embodiment Resolution Processing Unit 22 Super Resolution Parameter Setting Unit 23 of Image Processing Device of Embodiment 3 Super Resolution Parameter Storage Unit 24 of Image Processing Device of Embodiment 3 MTF Measurement Unit 25 of Image Processing Device of Embodiment 3 Image processing unit 101 of image processing apparatus of form 3 Scanner unit 102 CPU
103 RAM
104 ROM
105 Recording unit 106 Operation unit 107 Communication unit 200 Super-resolution processing in ROM 201 Image reading processing in ROM 202 Resolving power measurement processing in ROM 203 Communication processing in ROM 204 Work area in RAM 205 Non-volatile area in RAM Image number storage area 206 Non-volatile area target MTF value storage area 207 in RAM Non-volatile area MTF characteristic table storage area 208 RAM Non-volatile area scanner type storage area 300 RAM Image processing in Embodiment 1 of the present embodiment Apparatus 301 Image Processing Apparatus 302 in Embodiment 2 of the Present Embodiment Image Processing Apparatus 400 in Embodiment 3 of the Present Embodiment Control PC for MTF Adjustment

Claims (6)

Scanner means for phase Chi lifting the first resolution to output a plurality of low-resolution image data which are shifted from each other,
A super solution for generating image data having a second resolution higher than the first resolution by using a plurality of low resolution image data having the first resolution output from the scanner unit and having phases shifted from each other. Super-resolution processing means for executing image processing;
Resolution of the scanner unit is smaller than the pre-specified resolution, the as resolution of the low-resolution image data output by the scanner unit is resolving power the previously specified, is used in the super-resolution processing means and a determining means for determining a number of low-resolution image data,
The super-resolution processing means uses a low-resolution image data of the number determined by the determining means, the first resolution is rather high than the resolution, the a resolution of the image data with the pre-specified resolution the image processing apparatus according to claim and Turkey to generate a high-resolution image data having the second resolution. A table in which values indicating the resolution of low-resolution image data output by the scanner unit and values indicating the number of low-resolution image data used by the super-resolution processing unit necessary to realize the value are registered. Having a storage means for storing;
The image processing apparatus according to claim 1, wherein the determining unit determines the number of the low-resolution image data with reference to the table stored by the storing unit. Scanner means for phase Chi lifting the first resolution to output a plurality of low-resolution image data which are shifted from each other,
A super solution for generating image data having a second resolution higher than the first resolution by using a plurality of low resolution image data having the first resolution output from the scanner unit and having phases shifted from each other. Super-resolution processing means for executing image processing;
Measuring means for measuring the resolving power of the scanner means;
Resolution of the scanner means measured by said measuring means is less than the pre-specified resolution, as the resolution of the low resolution image data output by the scanner unit is resolution said previously specified, the greater and a determining means for determining a number of low-resolution image data used in the resolution process means,
The super-resolution processing means uses a low-resolution image data of the number determined by the determining means, the first resolution is rather high than the resolution, the a resolution of the image data having a prespecified resolution the image processing apparatus according to claim and Turkey to generate a high-resolution image data having the second resolution. A method for controlling an image processing apparatus having a scanner phase Chi lifting the first resolution to output a plurality of low-resolution image data which are shifted from each other,
Super-resolution for generating image data having a second resolution higher than the first resolution by using a plurality of low-resolution image data having the first resolution output from the scanner and having phases shifted from each other. A super-resolution processing step for performing processing;
Resolution of the scanner is smaller than the pre-specified resolution, as the resolution of the low resolution image data becomes the pre-specified resolution output by the scanner, a low resolution is used in the super-resolution processing step and a determination step of determining the number of image data,
The super-resolution processing step, using a low-resolution image data of the number determined in the determining step, the first resolution is rather high than the resolution, the a resolution of the image data having a prespecified resolution No. method of controlling an image processing apparatus according to claim and Turkey to generate a high-resolution image data having the second resolution. A method for controlling an image processing apparatus having a scanner phase Chi lifting the first resolution to output a plurality of low-resolution image data which are shifted from each other,
Super-resolution for generating image data having a second resolution higher than the first resolution by using a plurality of low-resolution image data having the first resolution output from the scanner and having phases shifted from each other. A super-resolution processing step for performing processing;
A measuring step for measuring the resolution of the scanner;
Resolution of the scanner, which is measured by the measuring step is smaller than the pre-specified resolution, as the resolution of the low resolution image data output by the scanner is resolution of the previously specified, the super-resolution and a determination step of determining the number of low-resolution image data used in the processing step,
The super-resolution processing step, using a low-resolution image data of the number determined in the determining step, the first resolution is rather high than the resolution, the a resolution of the image data having a prespecified resolution No. method of controlling an image processing apparatus according to claim and Turkey to generate a high-resolution image data having the second resolution.   A program for causing a computer to execute the control method of the image processing apparatus according to claim 4 or 5.

Images